TRANSFORMING TABULAR DATA INTO VISUALIZATIONS INTRAHEALTH INTERNATIONAL: STRENGTHENING HEALTH SYSTEMS & IMPROVING SERVICES IN TANZANIA USING DATA TRANSFORMING TABULAR DATA INTO VISUALIZATIONS

OUTLINE BACKGROUND PROBLEM SOLUTION PROCESS CHALLENGES WHERE WE ARE HEADED PROPOSED WAY FORWARD

IntraHealth Tanzania portfolio 2011-2016 1.. Tanzania HIV Prevention Project (THPP) 2. TZ/Family Planning outreach Program 3. Better Immunization Data registry 4. Public Sector Systems Strengthening (PS3) 5. Tanzania Health Network Program 6. Tanzania Open data collaborative (dLab) 7. Tohara Plus Technical program areas: HIV/AIDs , HRH, ICT, FP, GBV/VAC Donors: PEPFAR/CDC, DFID, USAID, BMGF, PEPFAR/MCC

THPP Goal Reduce the transmission of new HIV infections by supporting the MOHCDGEC/NACP to expand, strengthen and sustain the provision of optimum quality HTC, GBV/VAC and VMMC services for HIV prevention

PROBLEM: TRACKING CLIENTS DATA Clients service data is tracked using tabular format. This provides a very limited perspective on clients services.

SOLUTION 1. Graphs make it easy to view all data and make comparisons GBV HTC VMMC

SOLUTION 2. Geospatial visualization help us better understand Project coverage the impact we make Better ways to manage our resources Adding a geospatial component to the tabular data is a necessity in understanding; The distribution of clients in a region relative to the location of the nearest Health facility working with IntraHealth, Finding the percentage of a local population that is being served by IntraHealth through VMMC and other Projects. Assessing where unserved or underserved populations are located and identify additional health resources they need.

SOLUTION ON REACHING GAPS IDENTIFIED A detailed geotagged Health Facilities list Shapefiles Population Data Broken down to lowest administrative level such as a village Program Data HFR and NBS provide the data listed, IH has the Program Data Once these are combined (supported by dLab) we can then have the visualizated Program Data

PROCESS UNDERTAKEN Joining project data with population and geospatial data from the National Bureau of Statistics (NBS) and geotagged health facilities lists to have more complete picture. Matched the health facilities to their geospatial coordinates paints a clear picture of where IntraHealth facilities are clustered. Overlayed that information on a map that shows district level data.

Joining data from disparate sources can be challenging. CHALLENGES Joining data from disparate sources can be challenging. Solution: Revisit data sharing processes and work with partners to have common standards and cleaning methods. Additional capacity building. IntraHealth’s data has varied aggregated age bands, which keeps on changing overtime as per donors requirements. Solution: Longer term approach is to address this for all data consumers by partnerships with government to provide de-identified, disaggregated data. hence this precludes a direct comparison between services offered to certain population subsets year.

Locating populations that are underserved and reallocate resources. WHERE WE ARE HEADED Moving forward with understanding IntraHealth’s coverage compared to the total population. Granular population (denominator) for advanced analysis. Locating populations that are underserved and reallocate resources. Incorporate resource allocation datasets. Targeted outreach sensitization campaigns to reach the right places and right people. Data will drive evidence-based advocacy and policy making. Impact will be improvement in services at the lower-performing facilities. and to the target number of beneficiaries, thereby allowing IntraHealth to quantitatively assess the performance of each facility; , e.g. through increased staffing, extended facility hours, or services at new locations;

WAY FORWARD Improve future data collection: Data use project needs complete critical analysis on how future data collection strategies could be tailored to create a more robust product in the next iteration. Scale-up data partnerships for open data: Continue to intensify advocacy activities with respective ministries to ensure public data are collected in raw formats (not- dissagregated).

“It always seems impossible until it’s done” Thank you for listening! Nelson Mandela Thank you for listening!